Layered indexing for asynchronous retrieval of redundancy coded data

ABSTRACT

A multilayered index is implemented for data stored in a data storage system. The multilayered index may include a granular index that specifies the location of specific files or abstractions within the data storage system, while a skip table specifies segments of the abstractions, and may point to both the granular index and the data storage devices of the data storage system. In redundancy coded systems, the use of multilayered indices may enable asynchronous retrieval of data during normal or adverse operation (such as during periods of varying data availability).

CROSS REFERENCE TO RELATED APPLICATIONS

This application incorporates by reference for all purposes the full disclosure of co-pending U.S. patent application Ser. No. 14/789,783, filed Jul. 1, 2015, entitled “GRID ENCODED DATA STORAGE SYSTEMS FOR EFFICIENT DATA REPAIR” and co-pending U.S. patent application Ser. No. 14/741,409, filed Jun. 16, 2015, entitled “ADAPTIVE DATA LOSS MITIGATION FOR REDUNDANCY CODING SYSTEMS.”

BACKGROUND

Modern computer systems make extensive use of network computing and network data storage systems. Such use has proliferated in recent years, particularly in distributed or virtualized computer systems where multiple computer systems may share resources when performing operations and tasks associated with the computer systems. Such computer systems frequently utilize distributed data storage in multiple locations to store shared data items so that such data items may be made available to a plurality of consumers. The resources for network computing and network data storage are often provided by computing resource providers who leverage large-scale networks of computers, servers, and storage drives to enable customers to host and execute a variety of applications and web services. The usage of network computing and network data storage allows customers to efficiently and to adaptively satisfy their varying computing needs, whereby the computing and data storage resources that may be required by the customers are added or removed from a large pool provided by a computing resource provider as needed.

The proliferation of network computing and network data storage, as well as the attendant increase in the number of entities dependent on network computing and network data storage, have increased the frequency and amplitude of demand spikes, and in some cases, such demand spikes are not easily predicted. Database services optimized to scale for certain types of increased demand, such as payload size, may not necessarily be capable of handling demand on a different access, such as requested transaction rate.

BRIEF DESCRIPTION OF THE DRAWINGS

Various techniques will be described with reference to the drawings, in which:

FIG. 1 illustrates an example environment 100 in which redundancy coded data may be asynchronously retrieved when the data storage system is in a degraded state, in accordance with some embodiments;

FIG. 2 illustrates an example environment in which a multilayer index, such as an index that includes a skip table and a granular index, may be implemented in accordance with some embodiments;

FIG. 3 illustrates an example process for asynchronously retrieving data in a degraded data storage system using a multilayer index, in accordance with some embodiments;

FIG. 4 illustrates an example process for using a skip table to retrieve a data segment containing requested data in accordance with some embodiments;

FIG. 5 illustrates an example environment in which a computing resource service provider implements a data storage service, such as a grid storage service, to process and store data transacted therewith, in accordance with some embodiments;

FIG. 6 illustrates an example environment where a redundancy encoding technique is applied to data stored in durable storage in accordance with at least one embodiment;

FIG. 7 illustrates an example environment where a redundancy encoding technique is applied to data stored in durable storage in accordance with at least one embodiment;

FIG. 8 illustrates an example process for applying redundancy encoding techniques to data stored in durable storage in accordance with at least one embodiment; and

FIG. 9 illustrates an environment in which various embodiments can be implemented.

DETAILED DESCRIPTION

In one example, data stored on a data storage system, is redundancy coded so as to improve durability, availability, and other aspects of the storage thereof. In connection with the storage of the data, a multilayer index may be implemented to allow for asynchronous retrieval of, e.g., redundancy coded data shards, even when the redundancy coded data or the data storage system is partially unavailable (e.g., degraded).

The multilayer index may include two or more layered indices. In some embodiments, the multilayer index includes a granular index that tracks the location of each data abstraction (e.g., file, block range, or other structure) in the data storage system. In some of such embodiments, the location of each data abstraction is the same on each component or bundle on which that data abstraction is stored. For example, an offset or byte range of a redundancy coded portion of the data is consistent as between redundancy coded shards in the bundle. In such embodiments, the granular index may only track the specific location as generalized across the structure storing the data (e.g., the bundle), and the specific location may be used to locate the abstraction, or portion and/or redundancy coded form thereof, on any of the individual components (e.g., shards of the bundle) representing the abstraction.

As may be contemplated, if a given bundle or other structure holding a plurality of data abstractions includes a large number of small files, the size of the granular index may grow large, in some instances larger than the represented data. The multilayer index may also include a sparse or partially sparse index, such as a skip table as described in further detail below, that refers more generally to the locations of groups of abstractions. In some embodiments, the skip table may include references, such as data pointers, to the granular index, that describe the location within the granular index (e.g., start and end points), of a range or other plurality of abstractions. The skip table may further include additional pointers directly to the data storage devices, shards, or other components within which the abstractions actually reside, of each of those ranges. In embodiments where both types of pointers are implemented in the skip table, a data storage system may use the skip table to either loosely locate a range of abstractions directly on disk, tape, bundle, or other component, or refer to the granular index to allow for location of a specific abstraction.

In some embodiments, one or more unique identifiers are used and allocated to each abstraction in connection with indexing, storage, or both. In some of such embodiments, the identifiers are incremented or other otherwise unique for each abstraction, and the sort order is either predetermined or recorded at the time each identifier is assigned to a given abstraction. If the sort order is known, the individual identifier value assigned to a given abstraction may be used to located the requisite entry within the skip table and thus identify the segment to which the specific abstraction belongs.

In embodiments that redundancy code data so as to include identity shards from which an original form of the data or abstractions thereof are directly accessible, and derived shards that include a redundancy coded form of the data, and from which a quorum quantity of shards (whether other identity shards or derived shards) is sufficient to regenerate, using a redundancy code, the data in original form, if the data storage system and/or a set of shards representing data is degraded such that a given abstraction is not directly retrievable from, e.g., an associated identity shard, a skip table may be used in connection with the identifier to locate and generate the data. For example, in such a degraded scenario, the skip table may be held temporarily or otherwise cached in hot storage (e.g., temporary storage), and readily accessible, either in advance of an availability event or in connection with such an event. For a given requested abstraction with a unique identifier, the identifier value may be compared against the known sort order or sequence and the data segment location may be found using the skip table. As the skip table may contain direct references to the location within the data storage system components or shards of the segment, each portion of the segment (e.g., on a quorum quantity of remaining shards) is read, in some embodiments asynchronously relative to one another, and each segment portion is temporarily stored in a temporary store until such time as the portions are used to recreate the segment in original form. The specific abstraction may then be located in the recreated segment via linear scan, the use of the granular index if available, and the like.

It is contemplated that such a multilayer indexing implementation (e.g., using skip tables for coarse lookup and granular indices for finer lookup) may be used in normal operation, e.g., so as to improve speed and/or efficiency of retrieval. For example, the skip table may be used for a coarse lookup, then refer to the granular index for a fine lookup, which allows for precise location of the requested abstraction on disk, tape, shard, etc, even if all (or a usable quorum) of associated shards are accessible.

In the preceding and following description, various techniques are described. For purposes of explanation, specific configurations and details are set forth in order to provide a thorough understanding of possible ways of implementing the techniques. However, it will also be apparent that the techniques described below may be practiced in different configurations without the specific details. Furthermore, well-known features may be omitted or simplified to avoid obscuring the techniques being described.

FIG. 1 illustrates an example environment 100 in which redundancy coded data may be asynchronously retrieved when the data storage system is in a degraded state, in accordance with some embodiments.

Data stored on a data storage system may be redundancy coded so as to improve durability, availability, and other aspects of the storage thereof. In the illustrated example, data is stored in a bundle of shards 102, 104, 106, though a grid of shards may also be used. The illustrated bundle includes two identity shards 102, 104 and a derived shard 106, which collectively represent a set of data processed using a redundancy code, such as an erasure code, using techniques described herein as well as in the incorporated disclosures. The data may include a plurality of abstractions, such as files, extents, block ranges, byte ranges, trees, or other such data structures, which may be provided for storage in the data storage system (and in turn, the bundle of shards 102, 104, 106), by a client device connected to the system (e.g., through an application programming interface).

In the illustrated example, one of the identity shards 102 becomes unavailable, thus rendering the bundle degraded. However, in scenarios where the remaining shards 104, 106 may be processed with a redundancy code to generate the data presently unavailable from the identity shard 102, any of the abstractions which are represented in original form within the unavailable shard 102 may be located, retrieved, and processed in asynchronous fashion from remaining shards 104, 106, using an index 108 which, in some embodiments (such as illustrated below in at least FIG. 2), is a multilayer index. However, the techniques described in FIG. 1 may be implemented using any index, whether sparse or dense, single-layered or multilayer.

As illustrated, the index 108 is stored in connection with each shard 104, 106 (and 102, though it is not available in the unavailable shard 102). In some embodiments, the index may be redundancy coded and a redundancy coded portion 110 included in each shard, while in some embodiments, the index is stored separately from the shards. If the index 108 is redundancy coded, the portions of the index on each remaining shard 104, 106 are sent to a component of the implementing data storage system 112 to be processed and from which an original form of the index is recreated. Using the recreated index, the component (or other component) of the data storage system 112 locates the portions of some or all of the abstractions (e.g., in connection with a data retrieval request, whether from a client device or from another component of the data storage system 112, e.g., as a preemptive mitigation process) at the location 114 specified by the index 108 within the respective shards 104, 106. In some embodiments, any given portion or abstraction of the data is located in the same relative location (e.g., byte range, offset, etc.) across all shards of the bundle.

The redundancy coded portion of the abstraction in each shard 104, 106, is read and stored in temporary storage. In some embodiments, rather than being decoded synchronously as between each shard 104, 106, the respective portions in shards 104, 106 are read asynchronously relative to one another, and smaller shards 118, 120 representing the requested segment is repackaged therefrom and stored in temporary storage 122. At some point in time after a quorum quantity of the smaller shards 118, 120 is gathered in the temporary storage 122, a redundancy code (which may be the same redundancy code used to encode the data or segment in the first instance) is used to generate the original data 124.

FIG. 2 illustrates an example environment 200 in which a multilayer index, such as an index that includes a skip table and a granular index, may be implemented in accordance with some embodiments. As may be contemplated, if a given bundle or other structure holding a plurality of data abstractions includes a large number of small files, the size of the granular index may grow large, in some instances larger than the represented data. In connection with the storage of the data and implementation of an index, e.g., as shown in FIG. 1, a multilayer index 206, 208 may be implemented to allow for asynchronous retrieval of, e.g., redundancy coded data shards, even when the redundancy coded data or the data storage system is partially unavailable (e.g., degraded) (as shown in FIG. 1), as well as to reduce the size of an index cached in temporary storage in accordance with the techniques of FIG. 1.

As illustrated in FIG. 2, the multilayer index may include two or more layered indices 206, 208 and may be stored as part of 204 or in connection with set of shards, such as a bundle of shards as described elsewhere (e.g., within an identity shard 202 as shown in FIG. 2). In some embodiments, a skip table 206 includes pointers to locations (such as start and end points) within a granular index 208 of segments of data represented within the shards 202. In some embodiments, the skip table 206 may be cached in the temporary storage 218, either preemptively (as part of normal operation) or in connection with a degradation event, such as a partial loss of shard availability, network partition, etc.

The skip table 206 may be a sparse or partially sparse index, that refers more generally to the locations of groups of abstractions. In some embodiments, the skip table includes references, such as data pointers, to the granular index 208, that describe the location within the granular index 208 (e.g., start and end points), of a range or other plurality of abstractions. Such ranges may be segments 210 of the granular index 208, which correspond to a plurality of abstractions stored and arranged (according, for example, to a sort order by identifier value) on, e.g., a set of shards or a set of data storage devices 212. The skip table may further include additional pointers 214 directly to the data storage devices, shards, or other components 212 within which the abstractions indexed in the granular index 208, e.g., for each segment 210, actually reside, of each of those ranges (segments 210). In embodiments where both types of pointers are implemented in the skip table, a data storage system may use the skip table 206 to either loosely locate a segment or range of abstractions directly on disk, tape, bundle, or other component, or refer to the granular index 208 to allow for location of a specific abstraction.

In some embodiments, one or more unique identifiers are used and allocated to each abstraction in connection with indexing, storage, or both. In some of such embodiments, the identifiers are incremented or other otherwise unique for each abstraction, and the sort order is either predetermined or recorded at the time each identifier is assigned to a given abstraction. If the sort order is known, the individual identifier value assigned to a given abstraction may be used to located the requisite entry within the skip table and thus identify the segment to which the specific abstraction belongs. The individual identifier may be a counter, a randomly generated hash value, a functionally generated value that takes into account and/or encodes/expresses characteristics of the data and/or the structure in which it is stored, and the like.

In some embodiments, the multilayer index includes a granular index 208 that tracks the specific location of each data abstraction (e.g., file, block range, extent, or other specifically or arbitrarily defined structure) in the storing component (e.g., volume, shard, etc.) data storage system. The granular index 208 may include pointers to byte ranges, offsets, or other identifiers for each data abstraction represented. As previously discussed, in some of such embodiments, the location of each data abstraction within a given component (e.g., shard) is the same on each component or bundle on which that data abstraction is stored (e.g., other shards within the same bundle, across which the data is stored). For example, an offset or byte range of a redundancy coded portion of the data is consistent as between redundancy coded shards in the bundle. In such embodiments, the granular index may only track the specific location as generalized across the structure storing the data (e.g., the bundle), and the specific location may be used to locate the abstraction, or portion and/or redundancy coded form thereof, on any of the individual components (e.g., shards of the bundle) representing the abstraction.

In embodiments that redundancy coded data so as to include identity shards from which an original form of the data or abstractions thereof are directly accessible, and derived shards that include a redundancy coded form of the data, and from which a quorum quantity of shards (whether other identity shards or derived shards) is sufficient to regenerate, using a redundancy code, the data in original form, if the data storage system and/or a set of shards representing data is degraded such that a given abstraction is not directly retrievable from, e.g., an associated identity shard, the skip table 218 may be used in connection with the identifier (and/or value thereof) to locate and generate the data. For example, in such a degraded scenario, the skip table may be held temporarily or otherwise cached in hot storage (e.g., temporary storage 218), and readily accessible, either in advance of an availability event or in connection with such an event. For a given requested abstraction with a unique identifier, the identifier value may be compared against the known sort order or sequence and the data segment location may be found using the skip table 218. As the skip table may contain direct references to the location within the data storage system components or shards of the segment 210, each portion of the segment 210 (e.g., on a quorum quantity of remaining shards) is read from multiple shards, in some embodiments asynchronously relative to one another, and each segment portion is temporarily stored in a temporary store until such time as the portions are used to recreate the segment in original form. The specific abstraction may then be located in the recreated segment via linear scan, binary search for the abstraction, the use of the granular index if available, and the like.

For example, each abstraction (e.g., each object) may have a “magic string” or other identifier that uniquely identifies the identity, contents, and/or the like, of the abstraction to which it is associated. In such embodiments, the identifier may be searched for (via a binary search or by granular reference, e.g., using the granular index), scanned for (e.g., via linear scan), and the like. As another example, the space within the shard may include synchronization markers at known locations (e.g., offsets), each of which refers to the specific location (e.g., before the marker, after the marker, or on the market) within the space at which a given abstraction may be found (e.g., via the identifier previously mentioned, a file header, etc.). Such markers may be used to further improve efficiency at which a given abstraction may be located, and, as may be appreciated, such techniques may be combined.

In some embodiments, a given abstraction may reside in multiple identity shards, and in some cases, within different identity shards within different bundles. In such embodiments, a given indexing implementation may refer to each segment of the abstraction (e.g., within different bundles or shards) as separate abstractions, so as to simplify the location and retrieval of such separate abstractions, and may recombine the located segments into the requested abstraction.

It is contemplated that such a multilayer indexing implementation may be used in normal operation, e.g., so as to improve speed and/or efficiency of retrieval. For example, the skip table may be used for a coarse lookup for a given segment 210, then reference may be made to the granular index 208 for a fine lookup within the located segment 210, which allows for precise location of the requested abstraction on the media/shard 212.

FIG. 3 illustrates an example process 300 for asynchronously retrieving data in a degraded data storage system using a multilayer index, in accordance with some embodiments. At step 302, in response to a data request, e.g., from a client device, for data represented as a set of redundancy coded shards stored on, e.g., a data storage system, and in circumstances where the data is not directly readable from, e.g., an identity shard, but is reconstructible from other shards of the bundle, an index associated with the bundle is located, read, and in some instances, reconstituted. For example, the index may be stored as part of the redundancy coded data in the bundle of shards, and if an original form of the index is not available (e.g., in an identity shard), it is reconstructed in step 302.

At step 304, the index reconstituted or otherwise retrieved at step 302 is stored in temporary storage, such as that described in connection with FIGS. 1 and 2. As previously described, the act of storing the index may be performed preemptively (e.g., as part of nominal operation), or may be in connection with receiving information regarding the degradation of the bundle or data storage system (e.g., an availability event).

At step 306, the index is used to locate, in a quorum of remaining shards of the bundle, the redundancy coded form of the requested data from each shard of the quorum. As previously discussed, each portion of the redundancy coded form from each shard may be retrieved by the data storage system or other retrieval system independently and asynchronously relative to one another. As part of the retrieval, at step 308, the portions of redundancy coded portions of the data retrieved in step 306 are used by the data storage system to generate intermediate (smaller) shards therefrom, which may then be temporarily stored at step 310 in, e.g., temporary storage associated with the data storage system, for further processing by the data storage system at a later time, such as regeneration of the requested data at step 312.

FIG. 4 illustrates an example process 400 for using a skip table to retrieve a data segment containing requested data in accordance with some embodiments. A step 402, a skip table, such as described in connection with FIG. 2 above, is cached by a data storage system in temporary storage associated with the data storage system. The skip table is, in some embodiments, a part of a multilayer indexing scheme as described above in connection with at least FIG. 2.

At step 404, in response to receiving a data request for data that is represented by a set of redundancy coded shards, some of which are unavailable (but for which a quorum still remains), the skip table of 402 is used by the data storage system to locate a broad segment of the set of shards that includes the requested data. As discussed in connection with FIG. 2, the segment may be located directly by using a first set of pointers that locates the shards directly on the storage of the data storage system, or a granular index, also described in connection with FIG. 2, may be used to locate the segment. The segment may, in some embodiments, also include other data than the requested data, by operation of the “coarse” location by the skip table.

At step 406, the located segments are stored by the data storage system in temporary storage, and, as discussed in connection with FIGS. 1-3 above, the portions or fragments of the segments that reside in disparate shards of the set may be read asynchronously relative to one another. Once stored, at step 408, the original form of the data in the segments is reconstituted, such as by the data storage system, using, e.g., the redundancy code used to encode the data in the first instance. After reconstituting the segment data in step 408, at step 410, the requested data is specifically located with the segment. As previously described in FIGS. 1-3, this may be performed via a linear scan of the reconstituted segment, or by performing a secondary, finer lookup in an associated granular index.

FIG. 5 illustrates an example environment 500 in which a computing resource service provider implements a data storage service, such as a grid storage service, to process and store data transacted therewith, in accordance with some embodiments.

A customer, via a customer device 502, may connect via a network 504 to one or more services 506 provided by a computing resource service provider 518. In some embodiments, the computing resource service provider 518 may provide a distributed, virtualized and/or datacenter environment within which one or more applications, processes, services, virtual machines, and/or other such computer system entities may be executed. In some embodiments, the customer may be a person, or may be a process running on one or more remote computer systems, or may be some other computer system entity, user, or process. The customer device 502 and the network 504 may be similar to that described in connection with at least FIG. 1 above.

The command or commands to connect to the computer system instance may originate from an outside computer system and/or server, or may originate from an entity, user, or process on a remote network location, or may originate from an entity, user, or process within the computing resource service provider, or may originate from a user of the customer device 502, or may originate as a result of an automatic process or may originate as a result of a combination of these and/or other such origin entities. In some embodiments, the command or commands to initiate the connection to the computing resource service provider 518 may be sent to the services 506, without the intervention of the user of the services 506. The command or commands to initiate the connection to the services 506 may originate from the same origin as the command or commands to connect to the computing resource service provider 518 or may originate from another computer system and/or server, or may originate from a different entity, user, or process on the same or a different remote network location, or may originate from a different entity, user, or process within the computing resource service provider, or may originate from a different user of the customer device 502, or may originate as a result of a combination of these and/or other such same and/or different entities.

The customer device 502 may request connection to the computing resource service provider 518 via one or more connections and, in some embodiments, via one or more networks 504 and/or entities associated therewith, such as servers connected to the network, either directly or indirectly. The customer device 502 that requests access to the services 506 may, as previously discussed, include any device that is capable of connecting with a computer system via a network, including at least servers, laptops, mobile devices such as smartphones or tablets, other smart devices such as smart watches, smart televisions, set-top boxes, video game consoles and other such network-enabled smart devices, distributed computer systems and components thereof, abstracted components such as guest computer systems or virtual machines and/or other types of computing devices and/or components. The network 504, also as previously discussed, may include, for example, a local network, an internal network, a public network such as the Internet, or other networks such as those listed or described herein. The network may also operate in accordance with various protocols such as those listed or described herein.

The computing resource service provider 518 may provide access to one or more host machines as well as provide access to services such as virtual machine (VM) instances, automatic scaling groups, or file-based database storage systems as may be operating thereon. The services 506 may connect to or otherwise be associated with one or more storage services such as those described herein (e.g., the data storage service 514). The storage services may be configured to provide data storage for the services 506. In an embodiment, the computing resource service provider 518 may provide direct access to the one or more storage services for use by users and/or customers of the computing resource service provider. The storage services may manage storage of data on one or more block storage devices and/or may manage storage of data on one or more archival storage devices such as, for example, magnetic tapes.

For example, the computing resource service provider 518 may provide a variety of services 506 to the customer device 502, which may in turn communicate with the computing resource service provider 518 via an interface, which may be a web service interface, application programming interface (API), user interface, or any other type of interface. The services 506 provided by the computing resource service provider 518 may include, but may not be limited to, a virtual computer system service, a block-level data storage service, a cryptography service, an on-demand data storage service, a notification service, an authentication service, a policy management service, an archival storage service, a durable data storage service such as the data storage service 514, and/or other such services. Each of the services 506 provided by the computing resource service provider 518 may include one or more web service interfaces that enable the customer device 502 to submit appropriately configured API calls to the various services through web service requests. In addition, each of the services may include one or more service interfaces that enable the services to access each other (e.g., to enable a virtual computer system of the virtual computer system service to store data in or retrieve data from the on-demand data storage service or the data storage service 514, and/or to access one or more block-level data storage devices provided by the block-level data storage service).

The block-level data storage service may comprise one or more computing resources that collectively operate to store data for a user using block-level storage devices (and/or virtualizations thereof). The block-level storage devices of the block-level data storage service may, for example, be operationally attached to virtual computer systems provided by a virtual computer system service to serve as logical units (e.g., virtual drives) for the computer systems. A block-level storage device may enable the persistent storage of data used or generated by a corresponding virtual computer system where the virtual computer system service may be configured to only provide ephemeral data storage.

The computing resource service provider 518 may also include an on-demand data storage service. The on-demand data storage service may be a collection of computing resources configured to synchronously process requests to store and/or access data. The on-demand data storage service may operate using computing resources (e.g., databases) that enable the on-demand data storage service to locate and retrieve data quickly, to allow data to be provided in response to requests for the data. For example, the on-demand data storage service may maintain stored data in a manner such that, when a request for a data object is retrieved, the data object can be provided (or streaming of the data object can be initiated) in a response to the request. As noted, data stored in the on-demand data storage service may be organized into data objects. The data objects may have arbitrary sizes except, perhaps, for certain constraints on size. Thus, the on-demand data storage service may store numerous data objects of varying sizes. The on-demand data storage service may operate as a key value store that associates data objects with identifiers of the data objects that may be used by the user to retrieve or perform other operations in connection with the data objects stored by the on-demand data storage service.

Note that, unless otherwise specified, use of expressions regarding executable instructions (also referred to as code, applications, agents, etc.) performing operations that instructions do not ordinarily perform unaided (e.g., transmission of data, calculations, etc.) in the context of describing disclosed embodiments denote that the instructions are being executed by a machine, thereby causing the machine to perform the specified operations.

The services 506 may produce data, such as data 508 received from the customer device 502, which may be stored in the preliminary storage 512 as described above. In some embodiments, as previously mentioned, the data stored in the preliminary storage may be stored in unaltered form, such as in an identity shard. While the data is stored in the preliminary storage 512, the data 522 may be accessed by the services 506 (e.g., as a result of one or more API requests by the customer device 502) from the preliminary storage 512. After a determined period 250, such as described above in connection with FIG. 1, has passed and the data is migrated to a data storage service 514 provided by the computing resource service provider 518, the data may be accessed using the data storage service 514. In an embodiment where the data may be stored using redundancy encoding technique such as those described herein, the data storage service 514 may retrieve the data from any of the data volumes 516 and/or may reconstruct the data using the redundancy encoding techniques. The data volumes 516 may be magnetic tape, may be optical disks, or may be some other such storage media. As previously discussed and as further discussed herein, the data may be stored in identity shards that correspond individually to volumes, and may also be processed (using the redundancy encoding techniques) so as to create derived shards.

The data storage service 514 may store the data 522 in the preliminary storage 512 or may transmit a command that causes a different service (e.g., a block storage service or some other storage service such as those described herein) to store the data 522 in the preliminary storage 512. The data storage service 514 may also cause the data to be migrated from the preliminary storage 512 or may transmit a command that causes a different service to cause the data to be migrated from the preliminary storage 512. The data storage service 514 may also transmit a command or commands to cause a different service to perform other operations associated with making data objects eventually durable including, but not limited to, storing the data objects in the data shards, calculating derived shards, updating bundles, updating grids (i.e., updating horizontal, vertical, and other bundles of multiply bundled data), and/or other such operations.

In an embodiment, the preliminary storage 512 is a data storage volume such as, for example, a magnetic disk drive (e.g., a spinning disk drive or a solid state disk drive), computer system memory, magnetic tape, or some other optical storage device. In another embodiment, the preliminary storage 512 is a virtual and/or shared data storage volume that is mapped to a physical storage volume such as, for example, a disk drive, a solid state disk drive, computer system memory, magnetic tape, or some other optical storage device. As may be contemplated, the types of data storage volumes used for the preliminary storage 512 described herein are illustrative examples and other types of data storage volumes used for the preliminary storage 106 may be considered as within the scope of the present disclosure.

In an embodiment, the preliminary storage 512 is a plurality of storage devices that are used to redundantly store the data using techniques such as, for example, bundle encoding, grid encoding, or replicated storage. For example, the preliminary storage 512 may store the data by distributing the data to a plurality of data shards (e.g., putting a first portion of the data in a first data shard and a second portion of the data in a second data shard) and generating one or more derived shards based on those data shards. In another embodiment, the preliminary storage 512 is one or more storage devices that store redundant copies of the data as received. In yet another embodiment, the preliminary storage uses a combination of the storage techniques described herein by, for example, storing a single copy of the data for a first time period (e.g., thirty minutes), storing multiple copies of the data for a second time period (e.g., one day), using redundant storage techniques such as grid or bundle encoding to store the data for a third time period (e.g., thirty days), and then moving the data to more durable storage 516 using the data storage service 514 as described herein.

The set of data may be stored in the preliminary storage 512 in an unaltered form (e.g., not processed, compressed, indexed, or altered prior to storage). The set of data may also be stored in the preliminary storage 512 as, for example, original data (also referred to herein as an “identity shard”) such as the original data shards described herein. In an embodiment, the set of data stored in the preliminary storage 512 is stored without indexing and without any redundancy encoding. In another embodiment, the set of data stored in the preliminary storage 512 is stored with null redundancy encoding (i.e., a redundancy encoding that maps the data to itself). The data in preliminary storage may be stored as raw data, or may be bundle-encoded, or may be grid-encoded, or may be stored using some other method.

In an embodiment, data can be migrated from preliminary storage to the data storage service 514 as a result of an event such as, for example, a request by a customer to store the data in the data storage service 514. Other events may also be used to cause the migration of the data from preliminary storage 512 to the data storage service 514 such as, for example, events generated by a process, module, service, or application associated with the customer or associated with a computing resource service provider. In an illustrative example, a block storage service may maintain data storage in preliminary storage for a running virtual machine instance and, upon termination of the instance, may generate an event to migrate some or all of the data from preliminary storage to durable storage. The triggering event that causes the migration of data from preliminary storage may also be combined with an elapsed time as described above so that, for example, data may be stored in preliminary storage until an event occurs, but the data may also be migrated from preliminary storage if no event occurs prior to the elapsed time. As may be contemplated, the criteria for initiating the migration from preliminary storage described herein are illustrative examples and other such criteria for initiating the migration from preliminary storage may be considered as within the scope of the present disclosure.

As used herein, the durability of a data object may be understood to be an estimate of the probability that the data object will not unintentionally become permanently irretrievable (also referred to herein as “unavailable”). This durability is an estimated probability and is generally expressed as a percentage (e.g., 99.9999 percent). This durability is based on assumptions of probabilities of certain failures (e.g., the AFR of drives used to store the data) and may be based on an average failure rate, a maximum failure rate, a minimum failure rate, a mean failure rate, or some other such failure rate. The durability may be based on a statistical average of the failure over a collection of drives when there are many different drives and/or when there are many different types of drives. The durability may also be based on historical measurements of the failure of drives and/or statistical sampling of the historical measurements of the failure of drives. The durability may also be correlated with the probability that a data object will not unintentionally become unavailable such as, for example, basing the durability on the probability that a data object will unintentionally become unavailable. As may be contemplated, the methods of determining durability of data described herein are merely illustrative examples and other such methods of determining durability of data may be considered as within the scope of the present disclosure.

In an embodiment, a separate service 510 can be configured to monitor the elapsed time 520 associated with the data objects in preliminary storage 512 and, based on a desired durability, cause the data storage service 514 to initiate migration of the data objects from the preliminary storage 512 to the durable storage by, for example, transmitting a message to the data storage service. This separate service may operate asynchronously to enforce time limits for all such data stored in preliminary storage.

FIG. 6 illustrates an example environment 600 where a redundancy encoding technique is applied to data stored in durable storage as described in connection with FIG. 1 and in accordance with an embodiment. The redundancy encoding technique illustrated in FIG. 6 is an example of a grid encoding technique wherein each identity shard is part of a first set of one or more identity shards which may be bundled with one or more derived shards in a first group or bundle (i.e., in one dimension or direction) and each identity shard is also part of at least a second set of one or more identity shards which may be bundled with one or more other derived shards in a second bundle or group (i.e., in a second dimension or direction). As is illustrated in FIG. 6, a grid encoding technique is often implemented as a two-dimensional grid, with each shard being part of two bundles (i.e., both “horizontal” and “vertical” bundles). However, a grid encoding technique may also be implemented as a three-dimensional grid, with each shard being part of three bundles, or a four-dimensional grid, with each shard being part of four bundles, or as a larger-dimensional grid. Additional details of grid encoding techniques are described in U.S. patent application Ser. No. 14/789,783, filed Jul. 1, 2015, entitled “GRID ENCODED DATA STORAGE SYSTEMS FOR EFFICIENT DATA REPAIR” which is incorporated by reference herein.

In the example illustrated in FIG. 6, data 602 from preliminary storage is provided for storage in durable storage using a redundancy encoding technique with both horizontal derived shards and vertical derived shards. In the example illustrated in FIG. 6, a first datacenter 612 may contain data shards (denoted as a square shard with the letter “I”), horizontal derived shards (denoted as a triangular shard with the Greek letter “6” or delta), and vertical derived shards (denoted as an inverted triangle with the Greek letter “6”) all of which may be stored on durable storage volumes within the first datacenter 612. A second datacenter 614, which may be geographically and/or logically separate from the first datacenter 612, may also contain data shards, horizontal derived shards, and/or vertical derived shards. A third datacenter 616, which may be geographically and/or logically separate from the first datacenter 612 and from the second datacenter 614, may also contain data shards, horizontal derived shards, and/or vertical derived shards. As illustrated in FIG. 6, each of the three datacenters may be a single vertical bundle. In an embodiment, each of the datacenters can include multiple vertical bundles. As may be contemplated, the number of datacenters illustrated in FIG. 6 and/or the composition of the datacenters illustrated in FIG. 6 are merely illustrative examples and other numbers and/or compositions of datacenters may be considered as within the scope of the present disclosure. The datacenters may be co-located or may be located in one or more separate datacenter locations.

In the example illustrated in FIG. 6, the data 602 may be copied to a data shard 604 and, as a result of the change to the data in the data shard 604, a horizontal derived shard 606 associated with the data shard 604 may be updated so that the horizontal derived shard 606 may be used to reconstruct the data shard 604 in the event of a loss of the data shard 604. In the example illustrated in FIG. 6, the three shards enclosed by the dotted line (e.g., the data shard 604, the data shard 620, and the horizontal derived shard 606) are a horizontal bundle 618. In this example, the data shard 620 is not affected by the changes to the data shard 604 but the horizontal derived shard 606 may need to be updated as a result of the changes to the data shard 604.

Also as a result of the change to the data in the data shard 604, one or more vertical derived shards 608 related to the data shard 604 may also be updated so that the vertical derived shards 608 may be used to reconstruct the data shard 604 in the event of a loss of the data shard 604 and the horizontal derived shard 606. In the example illustrated in FIG. 6, the shards in datacenter 612 form a vertical bundle. In this example, the other data shards 622 in the vertical bundle and/or the horizontal derived shards 624 in the vertical bundle are not affected by the changes to the data shard 604 but the vertical derived shards 608 may need to be updated as a result of the changes to the data shard 604. Finally, as a result of the change to the horizontal derived shard 606, one or more vertical derived shards 610 related to the horizontal derived shard 606 in the vertical bundle in datacenter 616 may also be updated so that the vertical derived shards 610 may be used to reconstruct the horizontal derived shard 606 in the event of a loss of the horizontal derived shard 606 and the data shard 604.

FIG. 7 illustrates an example environment 700 where a redundancy encoding technique is applied to data stored in durable storage as described herein and in accordance with at least one embodiment. The redundancy encoding technique illustrated in FIG. 7 is an example of a bundle encoding technique wherein one or more identity shards (also referred to herein as “data shards”) may be bundled with one or more derived shards in a single group or dimension. Additional details of bundle encoding techniques are described in U.S. patent application Ser. No. 14/741,409, filed Jun. 16, 2015, entitled “ADAPTIVE DATA LOSS MITIGATION FOR REDUNDANCY CODING SYSTEMS,” which is incorporated by reference herein.

Data 702 from preliminary storage may be sent to a data storage system 704 for redundant storage. The data 702 may be provided from the preliminary storage by any entity capable of transacting data with a data storage system, such as over a network (including the Internet). Examples include physical computing systems (e.g., servers, desktop computers, laptop computers, thin clients, and handheld devices such as smartphones and tablets), virtual computing systems (e.g., as may be provided by the computing resource service provider using one or more resources associated therewith), services (e.g., such as those connecting to the data storage system 704 via application programming interface calls, web service calls, or other programmatic methods), and the like.

The data storage system 704 may be any computing resource or collection of such resources capable of processing data for storage, and interfacing with one or more resources to cause the storage of the processed data. Examples include physical computing systems (e.g., servers, desktop computers, laptop computers, thin clients, and handheld devices such as smartphones and tablets), virtual computing systems (e.g., as may be provided by the computing resource service provider using one or more resources associated therewith), services (e.g., such as those connecting to the data storage system 704 via application programming interface calls, web service calls, or other programmatic methods), and the like. In some embodiments, the resources of the data storage system 704, as well as the data storage system 704 itself, may be one or more resources of a computing resource service provider, such as that described in further detail below. In some embodiments, the data storage system 704 and/or the computing resource service provider provides one or more archival storage services and/or data storage services, such as those described herein, through which a client entity may provide data such as the data 702 for storage in preliminary storage and/or the data storage system 704.

Data 702 may include any quantity of data in any format. For example, the data 702 may be a single file or may include several files. The data 702 may also be encrypted by, for example, a component of the data storage system 704 after the receipt of the data 702 in response to a request made by a customer of the data storage system 704 and/or by a customer of computing resource service provider.

The data storage system 704 may sort one or more identity shards according to one or more criteria (and in the case where a plurality of criteria is used for the sort, such criteria may be sorted against sequentially and in any order appropriate for the implementation). Such criteria may be attributes common to some or all of the archives, and may include the identity of the customer, the time of upload and/or receipt (by the data storage system 704), archive size, expected volume and/or shard boundaries relative to the boundaries of the archives (e.g., so as to minimize the number of archives breaking across shards and/or volumes), and the like. As mentioned, such sorting may be performed so as to minimize the number of volumes on which any given archive is stored. Such techniques may be used, for example, to optimize storage in embodiments where the overhead of retrieving data from multiple volumes is greater than the benefit of parallelizing the retrieval from the multiple volumes. Information regarding the sort order may be persisted, for example, by the data storage system 704, for use in techniques described in further detail herein.

As previously discussed, in some embodiments, one or more indices may be generated in connection with, for example, the order in which the archives are to be stored, as determined in connection with the sorting mentioned immediately above. The index may be a single index or may be a multipart index, and may be of any appropriate architecture and may be generated according to any appropriate method. For example, the index may be a bitmap index, dense index, sparse index, or a reverse index. Embodiments where multiple indices are used may implement different types of indices according to the properties of the identity shard to be stored via the data storage system 704. For example, a data storage system 704 may generate a dense index for archives over a specified size (as the size of the index itself may be small relative to the number of archives stored on a given volume), and may also generate a sparse index for archives under that specified size (as the ratio of index size to archive size increases).

The data storage system 704 is connected to or includes one or more volumes 706 on which archives or identity shards may be stored. The generated indices for the archives may also be stored on the one or more volumes 706. The volumes 706 may be any container, whether logical or physical, capable of storing or addressing data stored therein. In some embodiments, the volumes 706 may map on a one-to-one basis with the data storage devices on which they reside (and, in some embodiments, may actually be the data storage devices themselves). In some embodiments, the size and/or quantity of the volumes 706 may be independent of the capacity of the data storage devices on which they reside (e.g., a set of volumes may each be of a fixed size such that a second set of volumes may reside on the same data storage devices as the first set). The data storage devices may include any resource or collection of resources, such as those of a computing resource service provider, that are capable of storing data, and may be physical, virtual, or some combination of the two.

As previously described, one or more indices may, in some embodiments, be generated for each volume of the plurality of volumes 706, and in such embodiments, may reflect the archives stored on the respective volume to which it applies. In embodiments where sparse indices are used, a sparse index for a given volume may point to a subset of archives stored or to be stored on that volume, such as those archives which may be determined to be stored on the volume based on the sort techniques mentioned previously. The subset of volumes to be indexed in the sparse index may be selected on any appropriate basis and for any appropriate interval. For example, the sparse index may identify the archives to be located at every x blocks or bytes of the volume (e.g., independently of the boundaries and/or quantity of the archives themselves). As another example, the sparse index may identify every nth archive to be stored on the volume. As may be contemplated, the indices (whether sparse or otherwise), may be determined prior to actually storing the archives on the respective volumes. In some embodiments, a space may be reserved on the volumes so as to generate and/or write the appropriate indices after the archives have been written to the volumes 706.

In some embodiments, the sparse indices are used in connection with information relating to the sort order of the archives so as to locate archives without necessitating the use of dense indices, for example, those that account for every archive on a given volume. Such sort order-related information may reside on the volumes 706 or, in some embodiments, on an entity separate from the volumes 706, such as in a data store or other resource of a computing resource service provider. Similarly, the indices may be stored on the same volumes 706 to which they apply, or, in some embodiments, separately from such volumes 706.

The archives may be stored, bit for bit (e.g., the “original data” of the archives), on a subset of the plurality of volumes 706. Also as mentioned, appropriate indices may also be stored on the applicable subset of the plurality of volumes 706. The original data of the archives is stored as a plurality of shards across a plurality of volumes, the quantity of which (either shards or volumes, which in some cases may have a one to one relationship) may be predetermined according to various factors, including the number of total shards that may be used to reconstruct the original data using a redundancy encode. In some embodiments, the number of volumes used to store the original data of the archives is the quantity of shards that may be used to reconstruct the original data from a plurality of shards generated by a redundancy code from the original data. As an example, FIG. 7 illustrates five volumes, three of which contain original data archives 708 and two of which contain derived data 710, such as redundancy encoded data. In the illustrated example, the redundancy code used may require any three shards to regenerate original data, and therefore, a quantity of three volumes may be used to write the original data (even prior to any application of the redundancy code).

The volumes 706 bearing the original data archives 708 may each contain or be considered as shards unto themselves. For example, the data 702 from preliminary storage may be copied directly only to a volume if, as described herein, it is stored in preliminary storage as an identity shard. In embodiments where the sort order-related information and/or the indices are stored on the applicable volumes 706, they may be included with the original data of the archives and stored therewith as shards, as previously mentioned. In the illustrated example, the original data archives 708 are stored as three shards (which may include the respective indices) on three associated volumes 706. In some embodiments, the original data archives 708 (and, in embodiments where the indices are stored on the volumes, the indices) are processed by an entity associated with, for example, the archival storage service, using a redundancy code, such as an erasure code, so as to generate the remaining shards, which contain encoded information rather than the original data of the original data archives. The original data archives 708 may be processed using the redundancy code at any time after being sorted, such as prior to being stored on the volumes, contemporaneously with such storage, or after such storage.

Such encoded information may be any mathematically computed information derived from the original data, and depends on the specific redundancy code applied. As mentioned, the redundancy code may include erasure codes (such as online codes, Luby transform codes, raptor codes, parity codes, Reed-Solomon codes, Cauchy codes, Erasure Resilient Systematic Codes, regenerating codes, or maximum distance separable codes) or other forward error correction codes. In some embodiments, the redundancy code may implement a generator matrix that implements mathematical functions to generate multiple encoded objects correlated with the original data to which the redundancy code is applied. In some of such embodiments, an identity matrix is used, wherein no mathematical functions are applied and the original data (and, if applicable, the indices) are allowed to pass straight through. In such embodiments, it may be therefore contemplated that the volumes bearing the original data (and the indices) may correspond to objects encoded from that original data by the identity matrix rows of the generator matrix of the applied redundancy code, while volumes bearing derived data correspond to other rows of the generator matrix. In the example illustrated in FIG. 7, the five volumes 706 include three volumes that have shards (e.g., identity shards) corresponding to the original data of the original data archives 708, while two have encoded shards corresponding to the derived data 710 (also referred to herein as “derived shards”). As illustrated in FIG. 7, the three original data archives 708, and the two encoded shards corresponding to the derived data 710 form a bundle 718 (denoted by the dashed line). In this example, the applied redundancy code may result in the data being stored in a “3:5” scheme, wherein any three shards of the five stored shards are required to regenerate the original data, regardless of whether the selected three shards contain the original data or the derived data.

In some embodiments, if one of the volumes 706 or a shard stored thereon is detected as corrupt, missing, or otherwise unavailable, a new shard may be generated using the redundancy code applied to generate the shard(s) in the first instance. The new shard may be stored on the same volume or a different volume, depending, for example, on whether the shard is unavailable for a reason other than the failure of the volume. The new shard may be generated by, for example, the data storage system 704, by using a quantity of the remaining shards that may be used to regenerate the original data (and the index, if applicable) stored across all volumes, regenerating that original data, and either replacing the portion of the original data corresponding to that which was unavailable (in the case that the unavailable shard contains original data), or reapplying the redundancy code so as to provide derived data for the new shard.

As previously discussed, in some embodiments, the new shard may be a replication of the unavailable shard, such as may be the case if the unavailable shard includes original data of the archive(s). In some embodiments, the new shard may be selected from a set of potential shards as generated by, for example, a generator matrix associated with the redundancy code, so as to differ in content from the unavailable shard (such as may be the case if the unavailable shard was a shard generated from the redundancy code, and therefore contains no original data of the archives). As discussed throughout this disclosure, the shards and/or volumes may be grouped and/or layered.

In some embodiments, retrieval of an archive stored in accordance with the techniques described herein may be requested by a client entity under control of a customer of the computing resource service provider and/or the archival storage service provided therefrom, as described in further detail throughout this disclosure. In response to the request, the data storage system 704 may locate, based on information regarding the sort order of the archives as stored on the volumes 706, the specific volume on which the archive is located. Thereafter, the index or indices may be used to locate the specific archive, whereupon it may be read from the volume and provided to a requesting client entity. In embodiments where sparse indices are employed, the sort order information may be used to locate the nearest location (or archive) that is sequentially prior to the requested archive, whereupon the volume is sequentially read from that location or archive until the requested archive is found. In embodiments where multiple types of indices are employed, the data storage system 704 may initially determine which of the indices includes the most efficient location information for the requested archive based on assessing the criteria used to deploy the multiple types of indices in the first instance. For example, if archives under a specific size are indexed in a sparse index and archives equal to or over that size are indexed in a parallel dense index, the data storage system 704 may first determine the size of the requested archive, and if the requested archive is larger than or equal to the aforementioned size boundary, the dense index may be used so as to more quickly obtain the precise location of the requested archive.

In some embodiments, the volumes 706 may be grouped such that each given volume has one or more cohorts 716. In such embodiments, a volume set (e.g., all of the illustrated volumes 706) may be implemented such that incoming archives to be stored on the volumes are apportioned to one or more failure-decorrelated subsets of the volume set. The failure-decorrelated subsets may be some combination of the volumes 706 of the volume subset, where the quantity of volumes correlates to a number of shards required for the implemented redundancy code. In the illustrated example, the overall volume set may comprise two failure-decorrelated subsets (volumes in a horizontal row) where a given constituent volume is paired with a cohort (e.g., the cohort 716). In some embodiments, the incoming archives are apportioned to one or more of the cohorts in the failure-decorrelated subset according to, for example, a predetermined sequence, based on one or more attributes of the incoming archives, and the like.

The illustrated example shows, for clarity, a pair-wise cohort scheme, though other schemes are contemplated as within scope of this disclosure, some of which are outlined in greater detail herein. In the illustrated example, some of the volumes of the volume set store original data of incoming archives (e.g., original data archives 708 and/or original data archives 712), while others store derived data (e.g., derived data 710 and derived data 714). The data storage system 704 may implement a number of failure-decorrelated subsets to which to store the incoming archives, and in the pair-wise scheme pictured, the volumes used for a given archive may differ based on some arbitrary or predetermined pattern. As illustrated, some archives may be apportioned to volumes of a given cohort that are assigned to one pattern, or failure-decorrelated subset as shown by original data archives 708 and derived data 710, while others are apportioned to volumes in a different pattern as shown by original data archives 712 and derived data 714. The patterns, as mentioned, may be arbitrary, predefined, and/or in some cases, sensitive to attributes of the incoming data. In some embodiments, patterns may not be used at all, and the member volumes of a given failure-decorrelated subset may be selected randomly from a pool of volumes in the volume set.

FIG. 8 illustrates an example process 800 for applying redundancy encoding techniques to data stored in durable storage as described herein in connection with FIG. 1 and in accordance with at least one embodiment. The example process 800 illustrated in FIG. 8 illustrates the processing, indexing, storing, and retrieving of data stored on a data storage system. The data may be retrieved from preliminary storage as described herein. The example process 800 illustrated in FIG. 8 may be used in conjunction with a grid encoding technique such that described in connection with FIG. 6, in conjunction with a bundle encoding technique such as that described in connection with FIG. 7, or with some other redundancy encoding technique. A data storage service such as the data storage service described herein may perform the example process 800 illustrated in FIG. 8.

At step 802, a resource of a data storage system, such as that implementing a redundancy code to store archives, determines which subset (e.g., quantity) of a plurality of volumes that may be used to recreate the original data to be stored, based on, for example, a redundancy code to be applied to the archives. For example, in accordance with the techniques described above in connection with FIG. 7, such information may be derived from predetermining the parameters of an erasure code with a specified ratio of shards that may be used to regenerate the original data from which they derive to the total number of shards generated from the application of the erasure code.

At step 804, original data, such as original data of archives received from customers of, for example, a data storage system or a computing resource service provider as described in further detail herein, is sorted by, for example, the data storage system or associated entity. For example, the sort order may be implemented on one or more attributes of the incoming data.

At step 806, one or more indices, such as sparse indices, are generated by, for example, the data storage system, for the original data. For example, there may be more than one index for a given volume, and such parallel indices may be of different types depending on the nature of the archives and/or original data being stored.

At step 808, the original data is stored, for example, by the data storage system, on the subset of volumes determined in connection with step 802, and in the order determined in step 804. Additionally, at step 810, the index generated in step 806 is stored, for example, by the data storage system, on an appropriate entity. For example, the index may be stored as part of a shard on which the original data is stored, or, in some embodiments, may be stored on a separate resource from that which persists the volume.

At step 812, the redundancy code is applied, for example, by the data storage system, to the determined subset of volumes (e.g., shards, as previously described herein), and additional shards containing data derived from the application of the redundancy code are stored on a predetermined quantity of volumes outside the subset determined in connection with step 802. For example, the ratio of volumes (e.g., shards as previously described herein) storing the original data to the overall quantity of volumes (including those storing the derived data generated in this step 812) may be prescribed by the recovery/encoding ratio of the redundancy code applied herein.

At step 814, in normal operation, requested data may be retrieved, for example, by the data storage system, directly from the subset of volumes storing the original data, without necessitating retrieval and further processing (e.g., by the redundancy code) from the volumes storing the derived data generated in step 812. However, at step 816, if any of the volumes are determined, for example, by the data storage system, to be unavailable, a replacement shard may be generated by the data storage system by reconstructing the original data from a quorum of the remaining shards, and re-encoding using the redundancy code to generate the replacement shard. The replacement shard may be the same or may be different from the shard detected as unavailable.

FIG. 9 illustrates aspects of an example environment 900 for implementing aspects in accordance with various embodiments. As will be appreciated, although a web-based environment is used for purposes of explanation, different environments may be used, as appropriate, to implement various embodiments. The environment includes an electronic client device 902, which can include any appropriate device operable to send and/or receive requests, messages, or information over an appropriate network 904 and, in some embodiments, convey information back to a user of the device. Examples of such client devices include personal computers, cell phones, handheld messaging devices, laptop computers, tablet computers, set-top boxes, personal data assistants, embedded computer systems, electronic book readers, and the like. The network can include any appropriate network, including an intranet, the Internet, a cellular network, a local area network, a satellite network or any other such network and/or combination thereof. Components used for such a system can depend at least in part upon the type of network and/or environment selected. Many protocols and components for communicating via such a network are well known and will not be discussed herein in detail. Communication over the network can be enabled by wired or wireless connections and combinations thereof. In this example, the network includes the Internet and/or other publicly-addressable communications network, as the environment includes a web server 906 for receiving requests and serving content in response thereto, although for other networks an alternative device serving a similar purpose could be used as would be apparent to one of ordinary skill in the art.

The illustrative environment includes at least one application server 908 and a data store 910. It should be understood that there can be several application servers, layers or other elements, processes or components, which may be chained or otherwise configured, which can interact to perform tasks such as obtaining data from an appropriate data store. Servers, as used herein, may be implemented in various ways, such as hardware devices or virtual computer systems. In some contexts, servers may refer to a programming module being executed on a computer system. As used herein, unless otherwise stated or clear from context, the term “data store” refers to any device or combination of devices capable of storing, accessing and retrieving data, which may include any combination and number of data servers, databases, data storage devices and data storage media, in any standard, distributed, virtual or clustered environment. The application server can include any appropriate hardware, software and firmware for integrating with the data store as needed to execute aspects of one or more applications for the client device, handling some or all of the data access and business logic for an application. The application server may provide access control services in cooperation with the data store and is able to generate content including, but not limited to, text, graphics, audio, video and/or other content usable to be provided to the user, which may be served to the user by the web server in the form of HyperText Markup Language (“HTML”), Extensible Markup Language (“XML”), JavaScript, Cascading Style Sheets (“CSS”), JavaScript Object Notation (JSON), and/or another appropriate client-side structured language. Content transferred to a client device may be processed by the client device to provide the content in one or more forms including, but not limited to, forms that are perceptible to the user audibly, visually and/or through other senses. The handling of all requests and responses, as well as the delivery of content between the client device 902 and the application server 908, can be handled by the web server using PHP: Hypertext Preprocessor (“PHP”), Python, Ruby, Perl, Java, HTML, XML, JSON, and/or another appropriate server-side structured language in this example. Further, operations described herein as being performed by a single device may, unless otherwise clear from context, be performed collectively by multiple devices, which may form a distributed and/or virtual system.

The data store 910 can include several separate data tables, databases, data documents, dynamic data storage schemes and/or other data storage mechanisms and media for storing data relating to a particular aspect of the present disclosure. For example, the data store illustrated may include mechanisms for storing production data 912 and user information 916, which can be used to serve content for the production side. The data store also is shown to include a mechanism for storing log data 914, which can be used for reporting, analysis or other such purposes. It should be understood that there can be many other aspects that may need to be stored in the data store, such as page image information and access rights information, which can be stored in any of the above listed mechanisms as appropriate or in additional mechanisms in the data store 910. The data store 910 is operable, through logic associated therewith, to receive instructions from the application server 908 and obtain, update or otherwise process data in response thereto. The application server 908 may provide static, dynamic, or a combination of static and dynamic data in response to the received instructions. Dynamic data, such as data used in web logs (blogs), shopping applications, news services and other such applications may be generated by server-side structured languages as described herein or may be provided by a content management system (“CMS”) operating on, or under the control of, the application server. In one example, a user, through a device operated by the user, might submit a search request for a certain type of item. In this case, the data store might access the user information to verify the identity of the user and can access the catalog detail information to obtain information about items of that type. The information then can be returned to the user, such as in a results listing on a web page that the user is able to view via a browser on the user device 902. Information for a particular item of interest can be viewed in a dedicated page or window of the browser. It should be noted, however, that embodiments of the present disclosure are not necessarily limited to the context of web pages, but may be more generally applicable to processing requests in general, where the requests are not necessarily requests for content.

Each server typically will include an operating system that provides executable program instructions for the general administration and operation of that server and typically will include a computer-readable storage medium (e.g., a hard disk, random access memory, read only memory, etc.) storing instructions that, when executed (i.e., as a result of being executed) by a processor of the server, allow the server to perform its intended functions.

The environment, in one embodiment, is a distributed and/or virtual computing environment utilizing several computer systems and components that are interconnected via communication links, using one or more computer networks or direct connections. However, it will be appreciated by those of ordinary skill in the art that such a system could operate equally well in a system having fewer or a greater number of components than are illustrated in FIG. 9. Thus, the depiction of the system 900 in FIG. 9 should be taken as being illustrative in nature and not limiting to the scope of the disclosure.

The various embodiments further can be implemented in a wide variety of operating environments, which in some cases can include one or more user computers, computing devices or processing devices which can be used to operate any of a number of applications. User or client devices can include any of a number of computers, such as desktop, laptop or tablet computers running a standard operating system, as well as cellular, wireless and handheld devices running mobile software and capable of supporting a number of networking and messaging protocols. Such a system also can include a number of workstations running any of a variety of commercially-available operating systems and other known applications for purposes such as development and database management. These devices also can include other electronic devices, such as dummy terminals, thin-clients, gaming systems and other devices capable of communicating via a network. These devices also can include virtual devices such as virtual machines, hypervisors and other virtual devices capable of communicating via a network.

Various embodiments of the present disclosure utilize at least one network that would be familiar to those skilled in the art for supporting communications using any of a variety of commercially-available protocols, such as Transmission Control Protocol/Internet Protocol (“TCP/IP”), User Datagram Protocol (“UDP”), protocols operating in various layers of the Open System Interconnection (“OSr”) model, File Transfer Protocol (“FTP”), Universal Plug and Play (“UpnP”), Network File System (“NFS”), Common Internet File System (“CIFS”) and AppleTalk. The network can be, for example, a local area network, a wide-area network, a virtual private network, the Internet, an intranet, an extranet, a public switched telephone network, an infrared network, a wireless network, a satellite network, and any combination thereof. In some embodiments, connection-oriented protocols may be used to communicate between network endpoints. Connection-oriented protocols (sometimes called connection-based protocols) are capable of transmitting data in an ordered stream. Connection-oriented protocols can be reliable or unreliable. For example, the TCP protocol is a reliable connection-oriented protocol. Asynchronous Transfer Mode (“ATM”) and Frame Relay are unreliable connection-oriented protocols. Connection-oriented protocols are in contrast to packet-oriented protocols such as UDP that transmit packets without a guaranteed ordering.

In embodiments utilizing a web server, the web server can run any of a variety of server or mid-tier applications, including Hypertext Transfer Protocol (“HTTP”) servers, FTP servers, Common Gateway Interface (“CGI”) servers, data servers, Java servers, Apache servers, and business application servers. The server(s) also may be capable of executing programs or scripts in response to requests from user devices, such as by executing one or more web applications that may be implemented as one or more scripts or programs written in any programming language, such as Java®, C, C# or C++, or any scripting language, such as Ruby, PHP, Perl, Python or TCL, as well as combinations thereof. The server(s) may also include database servers, including without limitation those commercially available from Oracle®, Microsoft®, Sybase®, and IBM® as well as open-source servers such as MySQL, Postgres, SQLite, MongoDB, and any other server capable of storing, retrieving, and accessing structured or unstructured data. Database servers may include table-based servers, document-based servers, unstructured servers, relational servers, non-relational servers or combinations of these and/or other database servers.

The environment can include a variety of data stores and other memory and storage media as discussed above. These can reside in a variety of locations, such as on a storage medium local to (and/or resident in) one or more of the computers or remote from any or all of the computers across the network. In a particular set of embodiments, the information may reside in a storage-area network (“SAN”) familiar to those skilled in the art. Similarly, any necessary files for performing the functions attributed to the computers, servers or other network devices may be stored locally and/or remotely, as appropriate. Where a system includes computerized devices, each such device can include hardware elements that may be electrically coupled via a bus, the elements including, for example, at least one central processing unit (“CPU” or “processor”), at least one input device (e.g., a mouse, keyboard, controller, touch screen or keypad) and at least one output device (e.g., a display device, printer or speaker). Such a system may also include one or more storage devices, such as disk drives, optical storage devices and solid-state storage devices such as random access memory (“RAM”) or read-only memory (“ROM”), as well as removable media devices, memory cards, flash cards, etc.

Such devices also can include a computer-readable storage media reader, a communications device (e.g., a modem, a network card (wireless or wired), an infrared communication device, etc.), and working memory as described above. The computer-readable storage media reader can be connected with, or configured to receive, a computer-readable storage medium, representing remote, local, fixed, and/or removable storage devices as well as storage media for temporarily and/or more permanently containing, storing, transmitting, and retrieving computer-readable information. The system and various devices also typically will include a number of software applications, modules, services or other elements located within at least one working memory device, including an operating system and application programs, such as a client application or web browser. In addition, customized hardware might also be used and/or particular elements might be implemented in hardware, software (including portable software, such as applets) or both. Further, connection to other computing devices such as network input/output devices may be employed.

Storage media and computer readable media for containing code, or portions of code, can include any appropriate media known or used in the art, including storage media and communication media, such as, but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information such as computer readable instructions, data structures, program modules or other data, including RAM, ROM, Electrically Erasable Programmable Read-Only Memory (“EEPROM”), flash memory or other memory technology, Compact Disc Read-Only Memory (“CD-ROM”), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other medium which can be used to store the desired information and which can be accessed by the system device. Based on the disclosure and teachings provided herein, a person of ordinary skill in the art will appreciate other ways and/or methods to implement the various embodiments.

The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. It will, however, be evident that various modifications and changes may be made thereunto without departing from the broader spirit and scope of the invention as set forth in the claims.

Other variations are within the spirit of the present disclosure. Thus, while the disclosed techniques are susceptible to various modifications and alternative constructions, certain illustrated embodiments thereof are shown in the drawings and have been described above in detail. It should be understood, however, that there is no intention to limit the invention to the specific form or forms disclosed, but on the contrary, the intention is to cover all modifications, alternative constructions and equivalents falling within the spirit and scope of the invention, as defined in the appended claims.

The use of the terms “a” and “an” and “the” and similar referents in the context of describing the disclosed embodiments (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. The term “connected,” when unmodified and referring to physical connections, is to be construed as partly or wholly contained within, attached to or joined together, even if there is something intervening. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein and each separate value is incorporated into the specification as if it were individually recited herein. The use of the term “set” (e.g., “a set of items”) or “subset” unless otherwise noted or contradicted by context, is to be construed as a nonempty collection comprising one or more members. Further, unless otherwise noted or contradicted by context, the term “subset” of a corresponding set does not necessarily denote a proper subset of the corresponding set, but the subset and the corresponding set may be equal.

Conjunctive language, such as phrases of the form “at least one of A, B, and C,” or “at least one of A, B and C,” unless specifically stated otherwise or otherwise clearly contradicted by context, is otherwise understood with the context as used in general to present that an item, term, etc., may be either A or B or C, or any nonempty subset of the set of A and B and C. For instance, in the illustrative example of a set having three members, the conjunctive phrases “at least one of A, B, and C” and “at least one of A, B and C” refer to any of the following sets: {(A)}, {B}, {C}, {A, B}, {A, C}, {B, C}, {A, B, C}. Thus, such conjunctive language is not generally intended to imply that certain embodiments require at least one of A, at least one of B and at least one of C each to be present.

Operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. Processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions and may be implemented as code (e.g., executable instructions, one or more computer programs or one or more applications) executing collectively on one or more processors, by hardware or combinations thereof. The code may be stored on a computer-readable storage medium, for example, in the form of a computer program comprising a plurality of instructions executable by one or more processors. The computer-readable storage medium may be non-transitory. In some embodiments, the code is stored on set of one or more non-transitory computer-readable storage media having stored thereon executable instructions that, when executed (i.e., as a result of being executed) by one or more processors of a computer system, cause the computer system to perform operations described herein. The set of non-transitory computer-readable storage media may comprise multiple non-transitory computer-readable storage media and one or more of individual non-transitory storage media of the multiple non-transitory computer-readable storage media may lack all of the code while the multiple non-transitory computer-readable storage media collectively store all of the code.

Accordingly, in some examples, computer systems are configured to implement one or more services that singly or collectively perform operations of processes described herein. Such computer systems may, for instance, be configured with applicable hardware and/or software that enable the performance of the operations. Further, computer systems that implement various embodiments of the present disclosure may, in some examples, be single devices and, in other examples, be distributed computer systems comprising multiple devices that operate differently such that the distributed computer system performs the operations described herein and such that a single device may not perform all operations.

The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate embodiments of the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

Embodiments of this disclosure are described herein, including the best mode known to the inventors for carrying out the invention. Variations of those embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate and the inventors intend for embodiments of the present disclosure to be practiced otherwise than as specifically described herein. Accordingly, the scope of the present disclosure includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the scope of the present disclosure unless otherwise indicated herein or otherwise clearly contradicted by context.

All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein. 

What is claimed is:
 1. A computer-implemented method, comprising: processing data to be stored in a plurality of volumes of durable storage of a data storage system by at least: using a redundancy code, redundancy coding at least the data to generate a bundle of bundle-encoded shards, a quorum quantity of which is sufficient to reconstruct original data associated with the bundle, such that a plurality of data objects associated with the data are each uniquely identified using a respective identifier and sorted for storage within the bundle according to the identifier, the plurality of data objects being a plurality of data files, the bundle including at least: identity shards, at least one identity shard of which contains an original form of the encrypted data; encoded shards representing a redundancy coded form of the encrypted data, and one or more indices, each index of the one or more indices comprising: a granular index that includes a plurality of pointers, each pointer of the plurality of pointers being associated with one or more locations of a first set of locations, within the bundle, of each data object of at least a subset of the plurality of data objects; and a skip table that includes: a plurality of sections, each section of the plurality of sections being associated with one or more plural subsets of the plurality of pointers, each plural subset being sequentially contiguous according to the identifier, and a second set of locations, within the bundle, of each section of the plurality of sections; and in response to receiving a retrieval request to retrieve at least one of the data objects, processing the retrieval request by at least: locating a requested data object within the original form of the data associated with the section.
 2. The computer-implemented method of claim 1, wherein redundancy coding of at least the data associated with the section includes redundancy coding the index in connection with the data associated with the section, so as to include an original form of the index in at least one of the identity shards and a redundancy coded form of the index in at least one of the encoded shards.
 3. The computer-implemented method of claim 1, wherein: each index of the one or more indices is associated with a different identity shard in the bundle; the first set of locations within the bundle is a first set of locations within an identity shard associated with the index; and the second set of locations within the bundle is a second set of locations within the identity shard associated with the index.
 4. The computer-implemented method of claim 3, wherein each index of the one or more indices is included within a respective identity shard associated with the index.
 5. The computer-implemented method of claim 1, further comprising generating a first shard from the first subset of the redundancy coded data and a second shard from the second subset of the redundancy coded data.
 6. The computer-implemented method of claim 5, further comprising storing the first shard and the second shard in temporary storage.
 7. The computer-implemented method of claim 5, wherein locating the requested data object within the original form of the data comprises locating the requested data object within the granular index.
 8. The computer-implemented method of claim 1, wherein, if the data object is available from the identity shards, locating the data object within the identity shards using at least the granular index.
 9. A system, comprising: at least one computing device configured to implement one or more services that: index a set of data stored on a data storage system as a set of redundancy coded shards and according to a sort order associated with a plurality of data objects within the set of data the plurality of data objects being a plurality of data files, the index comprising a first index and a second index; the first index including a first set of pointers to a first set of locations within the data storage system associated with each of a first plurality of subsets of the set of data; and the second index including: a second set of pointers to a second set of locations, each of which points to a plurality of the locations of the first set of locations; and a third set of pointers to a plurality of the pointers of the first set of pointers associated with the plurality of the locations of the first set; and locate a requested subset of the indexed set of data by at least: using the sort order and the second index, identifying a respective plurality of the first set of locations to which the request subset is associated; and retrieving a second subset of the indexed set of data from the identified plurality of the first set of locations, the second subset including at least the requested subset of the indexed data.
 10. The system of claim 9, wherein the data is stored in a bundle of redundancy coded shards.
 11. The system of claim 9, wherein the one or more services are further configured to locate the second subset of the indexed set of data in connection with receiving a data retrieval request for the requested subset of the indexed set of data.
 12. The system of claim 9, wherein the one or more services are further configured to locate the second subset of the indexed set of data in connection with receiving information that the requested subset of the indexed set of data is partially unavailable on the data storage system.
 13. The system of claim 12, wherein the partially unavailable indexed set of data is generable using a redundancy code used to redundancy code the indexed set of data for storage on the data storage system.
 14. The system of claim 9, wherein the second index is stored on and accessed from a first data storage device associated with the system and separate from a second data storage device on which the set of data is stored.
 15. A non-transitory computer-readable storage medium having stored thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to at least: for data stored as a set of redundancy-coded shards and in connection with an identifier associated with each data object of a plurality of data objects of the data, each data object being a data file, generate a first index and a second index: the first index including a first set of pointers to a first set of storage locations, each storage location of the first set of storage locations being associated with each of a first plurality of subsets of the data, each pointer of the first set of pointers mapping to a different storage location of the first set of storage locations; and the second index including: a second set of pointers to a second set of locations, each pointer of the second set of pointers referring to a plurality of the locations of the first set of locations; and a third set of pointers to a plurality of the pointers of the first set of pointers associated with the plurality of the locations of the first set; and retrieve a requested data object of the data by at least: using an identifier value of the requested subset of the data, a sort order associated with the identifier, and the second index, identifying a respective plurality of the first set of locations to which the requested data object is associated; and retrieving a second subset of the data from the identified plurality of the first set of locations, the second subset including at least the requested data object of the data.
 16. The non-transitory computer-readable storage medium of claim 15, wherein the instructions, as a result of being executed by the one or more processors, further cause the computer system to at least locate the requested data object within the retrieved second subset of the data using the first index.
 17. The non-transitory computer-readable storage medium of claim 15, wherein the instructions, as a result of being executed by the one or more processors, further cause the computer system to at least retrieve the requested data object of the data in connection with information that the requested data object of the data is partially unavailable.
 18. The non-transitory computer-readable storage medium of claim 15, wherein the instructions, as a result of being executed by the one or more processors, further cause the computer system to at least cache the second index in temporary storage.
 19. The computer-implemented method of claim 1, wherein the skip table is configured to be used for a coarse lookup for a given section such that reference can be made to the granular index for a fine lookup within the located segment to allow for precise location of the requested data object within a shard. 